ABSTRACT Significance: There are over 5 million people with insulin-treated diabetes in the United States who represent a disproportionately large share of the $237B in direct medical costs attributable to diabetes. The use of continuous glucose monitoring (CGM) has been shown to reduce HbA1c levels, a proven predictor of health outcomes within this population, with the greatest improvement achieved when CGM is coupled with continuous subcutaneous insulin infusion (CSII). The recent convergence of CGM and insulin pumps has enabled the first generation of automated insulin delivery (AID) systems, promising even better glycemic control for insulin-treated diabetes. However, current AID systems are complex, cumbersome, and expensive for the patient because they require multiple devices to be worn on the body: a glucose sensor, an insulin pump, and an insulin delivery catheter. We have developed a glucose sensing catheter that reduces the number of subcutaneous components from two to one, significantly reducing the size and complexity of these systems. By integrating the sensing catheter into a patch pump, we will further simplify the system by reducing the footprint, and enabling the first fully-integrated single component AID system. Resulting reductions in system size, complexity, and cost will increase adoption rates for AID, helping improve compliance, lower HbA1c levels, and improve health outcomes among people with type 1 diabetes. Preliminary Data: We have demonstrated glucose sensing can be performed at the site of insulin delivery. However, we have discovered that there is a glucose measurement artifact that occurs immediately after dispensing liquid (insulin or saline) from the cannula, likely caused by dilution of the surrounding interstitial fluid. Preliminary data suggest the magnitude of the artifact is related to the volume of the bolus. Specific Aims: This proposal represents the first phase of an effort to integrate the dual-use cannula with a miniaturized patch pump and an AID algorithm, taking advantage of a novel concentrated insulin to reduce CGM artifact size. In Specific Aim 1, we will reduce the impact of the dilution artifact through the use of ultraconcentrated insulin. We will characterize the impact of the artifact using smaller boluses of U500 insulin in a swine study. In Specific Aim 2, we will create a calibration algorithm based on a Kalman filter and a predictive model of future sensor values to further mitigate the dilution artifact. In Specific Aim 3, we will integrate the kinetics of the U-500 insulin into a model predictive control (MPC) AID algorithm developed by Oregon Health & Science University (OHSU) and optimize the algorithm to (1) incorporate a model of the kinetics of the Thermalin insulin and (2) eliminate any remaining dilution artifact that may still be present. We will evaluate the performance of the new calibration algorithm on the data collected in Aim 1 as well is in other human data that we have collected with the glucose sensing catheter. The MPC algorithm will be evaluated in silico using the OHSU virtual patient population in preparation for full integration into the Thermalin StampPump in phase 2 of this proposal. In summary, this collaborative effort between PDT, OHSU, and Thermalin brings together the only published amperometric glucose sensing catheter with a fault-tolerant AID algorithm and the only rapid, concentrated insulin. In short, we are the only team currently capable of providing this novel solution for a unified automated insulin delivery device.